Leisure Satisfaction and Life Satisfaction: Examining the Mediating Roles of Self-Rated Physical Health and Mental Health
Bibliographic record
Abstract
Researchers have studied leisure satisfaction and life satisfaction in different eras (Brown & Frankel, 1993; Neal et al., 1999; Ragheb & Griffith, 1982). A recent study demonstrated that leisure activities and life satisfaction correlate positively (Kim et al., 2022). However, limited information is available regarding the explanatory mechanisms underlying this connection. Drawing from the bottom-up spillover theory proposed by Andrews & Withey (1976), this research examines two potential explanatory mechanisms, self-rated physical health (SRPH) and self-rated mental health (SRMH), which could help explain the relationship between leisure satisfaction and overall life satisfaction. The current study uses population-level secondary data from Statistics Canada and the Canadian Community Health Survey (CCHS) (n = 113,290). The research suggests three hypotheses: (i) that leisure satisfaction has a positive relationship with life satisfaction; (ii) that self-rated physical health will positively mediate the association of life satisfaction and leisure satisfaction; and (iii) Self-rated mental health will operate as a positive mediator in the relationship between life satisfaction and leisure satisfaction. Measures, such as leisure satisfaction (e.g., “How satisfied are you with your leisure activities?”), life satisfaction (“How satisfied are you with your overall life?”), SRPH and SRMH were obtained from the 2017-2018 CCHS. Results from the regression analysis revealed that leisure satisfaction was a significant predictor of life satisfaction. Self-rated physical and mental health also partially mediated this relationship. This research contributes to the growing knowledge of the intricate interplay between leisure, mental and physical health, and overall life satisfaction. Understanding these relationships has implications for interventions and policies to enhance individuals' well-being by considering the role of leisure activities and their impact on mental and physical health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".